Implications of mutational spectrum in myelodysplastic syndromes based on targeted next-generation sequencing

Abstract

Myelodysplastic syndromes (MDS) are a group of myeloid hematological malignancies, with a high risk of progression to acute myeloid leukemia (AML). To explore the role of acquired mutations in MDS, 111 MDS-associated genes were screened using next-generation sequencing (NGS), in 125 patients. One or more mutations were detected in 84% of the patients. Some gene mutations are specific for MDS and were associated with disease subtypes, and the patterns of mutational pathways could be associated with progressive MDS. The patterns, frequencies and functional pathways of gene mutations are different, but somehow related, between MDS and AML. Multivariate analysis suggested that patients with ≥ 2 mutations had poor progression-free survival, while GATA1/GATA2, DNMT3A and KRAS/NRAS mutations were associated with poor overall survival. Based on a novel system combining IPSS-R and molecular markers, these MDS patients were further divided into 3 more accurate prognostic subgroups. A panel of 11 target genes was proposed for genetic profiling of MDS. The study offers new insights into the molecular signatures of MDS and the genetic consistency between MDS and AML. Furthermore, results indicate that MDS could be classified by mutation combinations to guide the administration of individualized therapeutic interventions.

Keywords: mutational spectrum; myelodysplastic syndromes; next-generation sequencing; risk stratification.

Figure 1. The genomic architecture of MDS

(a) Distribution of mutations in 125 MDS patients. Red boxes indicate mutations. (b) Frequencies of mutations identified in the cohort of 125 subjects, divided according to MDS subtype.

Figure 2. Specificity of mutations in MDS compared with healthy donators

(a) Correlations between gene mutations and chromosomes. (b) Correlations between gene mutations and IPSS-R risk stratifications. (c) Correlations between gene mutations and WHO classifications. Only those associations with a q value (false discovery rate adjusted p value) < 0.1 were shown. Associations are colored by odds ratio. Red colors label genes that were co-mutated in MDS more than expected, and blue colors label mutually exclusive gene mutations in MDS. Gene names are color coded by the different functional pathways below the figure. Due to a high SNP in healthy donators, the results of mutually exclusive genes had little meaning and the co-mutated genes were emphasized.

Figure 3

(a) Distribution of the number of co-occurring mutations (including point mutations and indels) relative to MDS subtypes. (b) The number of mutations involved in common functional pathways classified according to different WHO subtypes.

Figure 4. Kaplan-Meier curves of overall survival (OS) and progression free survival PFS

(a-c) Patients with GATA1/GATA2, TP53 and DNMT3A mutations had worse OS than wild type groups. (d-g) Patients with RUNX1, KRAS/NRAS, SRSF2 and TET2 mutations had worse PFS than wild type groups. (h) Patients with ≥ 2 mutations tended to have shorter PFS than those with < 2 mutations. OS and PFS were stratified by univariate prognostic factors. P values were calculated using the log-rank test.

Figure 5. Kaplan-Meier curves of survival according to the IPSS-R and IPSS-R-M systems

(a, c) Kaplan-Meier curves of OS. (b, d) Kaplan-Meier curves of PFS.